Retour à Deep Neural Networks with PyTorch
Avis et commentaires pour l'étudiant pour Deep Neural Networks with PyTorch par IBM
4.7
17 notes
À propos du cours
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered.
Learning Outcomes:
After completing this course, learners will be able to:
• explain and apply their knowledge of Deep Neural Networks and related machine learning methods
• know how to use Python libraries such as PyTorch for Deep Learning applications
• build Deep Neural Networks using PyTorch
Meilleurs avis
Filtrer par :
1 - 2 sur 2 Examens pour Deep Neural Networks with PyTorch
par Shinhoo K
•Nov 17, 2019
Awesome! This course gives me the basic workflow for using machine learning technique in my research! The materials in the form of Jupyter lab really help!
par Pavan D
•Nov 19, 2019
very intuitive and in depth
Coursera propose un accès universel à la meilleure formation au monde,
en partenariat avec des universités et des organisations du plus haut niveau, pour proposer des cours en ligne.
© 2019 Coursera Inc. Tous droits réservés.
